Overview

Brought to you by YData

Dataset statistics

Number of variables25
Number of observations103904
Missing cells310
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory45.8 MiB
Average record size in memory462.2 B

Variable types

Numeric19
Categorical6

Alerts

Arrival Delay in Minutes is highly overall correlated with Departure Delay in MinutesHigh correlation
Class is highly overall correlated with TypeofTravel and 1 other fieldsHigh correlation
Cleanliness is highly overall correlated with FoodandDrink and 2 other fieldsHigh correlation
Departure Delay in Minutes is highly overall correlated with Arrival Delay in MinutesHigh correlation
Ease of Online booking is highly overall correlated with InflightWifiServiceHigh correlation
FoodandDrink is highly overall correlated with Cleanliness and 2 other fieldsHigh correlation
Inflight entertainment is highly overall correlated with Cleanliness and 2 other fieldsHigh correlation
Inflight service is highly overall correlated with On-board serviceHigh correlation
InflightWifiService is highly overall correlated with Ease of Online booking and 1 other fieldsHigh correlation
On-board service is highly overall correlated with Inflight serviceHigh correlation
Online boarding is highly overall correlated with satisfactionHigh correlation
Seat comfort is highly overall correlated with Cleanliness and 2 other fieldsHigh correlation
TypeofTravel is highly overall correlated with ClassHigh correlation
satisfaction is highly overall correlated with Class and 2 other fieldsHigh correlation
Unnamed: 0 is uniformly distributedUniform
id is uniformly distributedUniform
Unnamed: 0 has unique valuesUnique
id has unique valuesUnique
InflightWifiService has 3103 (3.0%) zerosZeros
Departure/Arrival time convenient has 5300 (5.1%) zerosZeros
Ease of Online booking has 4487 (4.3%) zerosZeros
Online boarding has 2428 (2.3%) zerosZeros
Departure Delay in Minutes has 58668 (56.5%) zerosZeros
Arrival Delay in Minutes has 58159 (56.0%) zerosZeros

Reproduction

Analysis started2025-10-22 22:55:41.334642
Analysis finished2025-10-22 22:56:13.520103
Duration32.19 seconds
Software versionydata-profiling vv4.17.0
Download configurationconfig.json

Variables

Unnamed: 0
Real number (ℝ)

Uniform  Unique 

Distinct103904
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51951.5
Minimum0
Maximum103903
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size811.9 KiB
2025-10-22T16:56:13.640894image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5195.15
Q125975.75
median51951.5
Q377927.25
95-th percentile98707.85
Maximum103903
Range103903
Interquartile range (IQR)51951.5

Descriptive statistics

Standard deviation29994.646
Coefficient of variation (CV)0.5773586
Kurtosis-1.2
Mean51951.5
Median Absolute Deviation (MAD)25976
Skewness0
Sum5.3979687 × 109
Variance8.9967876 × 108
MonotonicityStrictly increasing
2025-10-22T16:56:13.722643image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1038871
 
< 0.1%
1038861
 
< 0.1%
1038851
 
< 0.1%
1038841
 
< 0.1%
1038831
 
< 0.1%
1038821
 
< 0.1%
1038811
 
< 0.1%
1038801
 
< 0.1%
1038791
 
< 0.1%
1038781
 
< 0.1%
Other values (103894)103894
> 99.9%
ValueCountFrequency (%)
01
< 0.1%
11
< 0.1%
21
< 0.1%
31
< 0.1%
41
< 0.1%
51
< 0.1%
61
< 0.1%
71
< 0.1%
81
< 0.1%
91
< 0.1%
ValueCountFrequency (%)
1039031
< 0.1%
1039021
< 0.1%
1039011
< 0.1%
1039001
< 0.1%
1038991
< 0.1%
1038981
< 0.1%
1038971
< 0.1%
1038961
< 0.1%
1038951
< 0.1%
1038941
< 0.1%

id
Real number (ℝ)

Uniform  Unique 

Distinct103904
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64924.211
Minimum1
Maximum129880
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size811.9 KiB
2025-10-22T16:56:13.803028image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6593.15
Q132533.75
median64856.5
Q397368.25
95-th percentile123409.7
Maximum129880
Range129879
Interquartile range (IQR)64834.5

Descriptive statistics

Standard deviation37463.812
Coefficient of variation (CV)0.57703917
Kurtosis-1.1984401
Mean64924.211
Median Absolute Deviation (MAD)32410
Skewness0.0028642483
Sum6.7458852 × 109
Variance1.4035372 × 109
MonotonicityNot monotonic
2025-10-22T16:56:13.884713image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
542531
 
< 0.1%
923231
 
< 0.1%
1225281
 
< 0.1%
67371
 
< 0.1%
1105911
 
< 0.1%
354921
 
< 0.1%
93451
 
< 0.1%
1242791
 
< 0.1%
593391
 
< 0.1%
151761
 
< 0.1%
Other values (103894)103894
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
21
< 0.1%
31
< 0.1%
41
< 0.1%
51
< 0.1%
61
< 0.1%
71
< 0.1%
81
< 0.1%
91
< 0.1%
101
< 0.1%
ValueCountFrequency (%)
1298801
< 0.1%
1298791
< 0.1%
1298781
< 0.1%
1298751
< 0.1%
1298741
< 0.1%
1298731
< 0.1%
1298711
< 0.1%
1298701
< 0.1%
1298691
< 0.1%
1298671
< 0.1%

Gender
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.4 MiB
Female
52727 
Male
51177 

Length

Max length6
Median length6
Mean length5.0149176
Min length4

Characters and Unicode

Total characters521070
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMale
2nd rowMale
3rd rowFemale
4th rowFemale
5th rowMale

Common Values

ValueCountFrequency (%)
Female52727
50.7%
Male51177
49.3%

Length

2025-10-22T16:56:13.960844image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-10-22T16:56:14.049752image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
female52727
50.7%
male51177
49.3%

Most occurring characters

ValueCountFrequency (%)
e156631
30.1%
a103904
19.9%
l103904
19.9%
F52727
 
10.1%
m52727
 
10.1%
M51177
 
9.8%

Most occurring categories

ValueCountFrequency (%)
(unknown)521070
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e156631
30.1%
a103904
19.9%
l103904
19.9%
F52727
 
10.1%
m52727
 
10.1%
M51177
 
9.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown)521070
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e156631
30.1%
a103904
19.9%
l103904
19.9%
F52727
 
10.1%
m52727
 
10.1%
M51177
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown)521070
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e156631
30.1%
a103904
19.9%
l103904
19.9%
F52727
 
10.1%
m52727
 
10.1%
M51177
 
9.8%

CustomerType
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size6.3 MiB
Loyal Customer
84923 
disloyal Customer
18981 

Length

Max length17
Median length14
Mean length14.548035
Min length14

Characters and Unicode

Total characters1511599
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLoyal Customer
2nd rowdisloyal Customer
3rd rowLoyal Customer
4th rowLoyal Customer
5th rowLoyal Customer

Common Values

ValueCountFrequency (%)
Loyal Customer84923
81.7%
disloyal Customer18981
 
18.3%

Length

2025-10-22T16:56:14.100227image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-10-22T16:56:14.139565image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
customer103904
50.0%
loyal84923
40.9%
disloyal18981
 
9.1%

Most occurring characters

ValueCountFrequency (%)
o207808
13.7%
l122885
 
8.1%
s122885
 
8.1%
103904
 
6.9%
a103904
 
6.9%
C103904
 
6.9%
y103904
 
6.9%
e103904
 
6.9%
u103904
 
6.9%
t103904
 
6.9%
Other values (5)330693
21.9%

Most occurring categories

ValueCountFrequency (%)
(unknown)1511599
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o207808
13.7%
l122885
 
8.1%
s122885
 
8.1%
103904
 
6.9%
a103904
 
6.9%
C103904
 
6.9%
y103904
 
6.9%
e103904
 
6.9%
u103904
 
6.9%
t103904
 
6.9%
Other values (5)330693
21.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1511599
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o207808
13.7%
l122885
 
8.1%
s122885
 
8.1%
103904
 
6.9%
a103904
 
6.9%
C103904
 
6.9%
y103904
 
6.9%
e103904
 
6.9%
u103904
 
6.9%
t103904
 
6.9%
Other values (5)330693
21.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1511599
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o207808
13.7%
l122885
 
8.1%
s122885
 
8.1%
103904
 
6.9%
a103904
 
6.9%
C103904
 
6.9%
y103904
 
6.9%
e103904
 
6.9%
u103904
 
6.9%
t103904
 
6.9%
Other values (5)330693
21.9%

Age
Real number (ℝ)

Distinct75
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.379706
Minimum7
Maximum85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size811.9 KiB
2025-10-22T16:56:14.198682image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile14
Q127
median40
Q351
95-th percentile64
Maximum85
Range78
Interquartile range (IQR)24

Descriptive statistics

Standard deviation15.114964
Coefficient of variation (CV)0.38382622
Kurtosis-0.71956812
Mean39.379706
Median Absolute Deviation (MAD)12
Skewness-0.0045161271
Sum4091709
Variance228.46213
MonotonicityNot monotonic
2025-10-22T16:56:14.286887image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
392969
 
2.9%
252798
 
2.7%
402574
 
2.5%
442482
 
2.4%
422457
 
2.4%
412456
 
2.4%
222351
 
2.3%
232346
 
2.3%
452339
 
2.3%
472329
 
2.2%
Other values (65)78803
75.8%
ValueCountFrequency (%)
7562
0.5%
8640
0.6%
9692
0.7%
10683
0.7%
11678
0.7%
12635
0.6%
13633
0.6%
14707
0.7%
15818
0.8%
16899
0.9%
ValueCountFrequency (%)
8517
 
< 0.1%
8078
 
0.1%
7942
 
< 0.1%
7833
 
< 0.1%
7787
0.1%
7645
 
< 0.1%
7561
 
0.1%
7447
 
< 0.1%
7351
 
< 0.1%
72201
0.2%

TypeofTravel
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size6.3 MiB
Business travel
71655 
Personal Travel
32249 

Length

Max length15
Median length15
Mean length15
Min length15

Characters and Unicode

Total characters1558560
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPersonal Travel
2nd rowBusiness travel
3rd rowBusiness travel
4th rowBusiness travel
5th rowBusiness travel

Common Values

ValueCountFrequency (%)
Business travel71655
69.0%
Personal Travel32249
31.0%

Length

2025-10-22T16:56:14.357732image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-10-22T16:56:14.395576image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
travel103904
50.0%
business71655
34.5%
personal32249
 
15.5%

Most occurring characters

ValueCountFrequency (%)
s247214
15.9%
e207808
13.3%
r136153
8.7%
a136153
8.7%
l136153
8.7%
103904
6.7%
n103904
6.7%
v103904
6.7%
i71655
 
4.6%
B71655
 
4.6%
Other values (5)240057
15.4%

Most occurring categories

ValueCountFrequency (%)
(unknown)1558560
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s247214
15.9%
e207808
13.3%
r136153
8.7%
a136153
8.7%
l136153
8.7%
103904
6.7%
n103904
6.7%
v103904
6.7%
i71655
 
4.6%
B71655
 
4.6%
Other values (5)240057
15.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1558560
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s247214
15.9%
e207808
13.3%
r136153
8.7%
a136153
8.7%
l136153
8.7%
103904
6.7%
n103904
6.7%
v103904
6.7%
i71655
 
4.6%
B71655
 
4.6%
Other values (5)240057
15.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1558560
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s247214
15.9%
e207808
13.3%
r136153
8.7%
a136153
8.7%
l136153
8.7%
103904
6.7%
n103904
6.7%
v103904
6.7%
i71655
 
4.6%
B71655
 
4.6%
Other values (5)240057
15.4%

Class
Categorical

High correlation 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.4 MiB
Business
49665 
Eco
46745 
Eco Plus
7494 

Length

Max length8
Median length8
Mean length5.7505678
Min length3

Characters and Unicode

Total characters597507
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEco Plus
2nd rowBusiness
3rd rowBusiness
4th rowBusiness
5th rowBusiness

Common Values

ValueCountFrequency (%)
Business49665
47.8%
Eco46745
45.0%
Eco Plus7494
 
7.2%

Length

2025-10-22T16:56:14.447908image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-10-22T16:56:14.489706image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
eco54239
48.7%
business49665
44.6%
plus7494
 
6.7%

Most occurring characters

ValueCountFrequency (%)
s156489
26.2%
u57159
 
9.6%
E54239
 
9.1%
c54239
 
9.1%
o54239
 
9.1%
B49665
 
8.3%
i49665
 
8.3%
e49665
 
8.3%
n49665
 
8.3%
7494
 
1.3%
Other values (2)14988
 
2.5%

Most occurring categories

ValueCountFrequency (%)
(unknown)597507
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s156489
26.2%
u57159
 
9.6%
E54239
 
9.1%
c54239
 
9.1%
o54239
 
9.1%
B49665
 
8.3%
i49665
 
8.3%
e49665
 
8.3%
n49665
 
8.3%
7494
 
1.3%
Other values (2)14988
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown)597507
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s156489
26.2%
u57159
 
9.6%
E54239
 
9.1%
c54239
 
9.1%
o54239
 
9.1%
B49665
 
8.3%
i49665
 
8.3%
e49665
 
8.3%
n49665
 
8.3%
7494
 
1.3%
Other values (2)14988
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown)597507
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s156489
26.2%
u57159
 
9.6%
E54239
 
9.1%
c54239
 
9.1%
o54239
 
9.1%
B49665
 
8.3%
i49665
 
8.3%
e49665
 
8.3%
n49665
 
8.3%
7494
 
1.3%
Other values (2)14988
 
2.5%

FlightDistance
Real number (ℝ)

Distinct3802
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1189.4484
Minimum31
Maximum4983
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size811.9 KiB
2025-10-22T16:56:14.550764image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile175
Q1414
median843
Q31743
95-th percentile3383
Maximum4983
Range4952
Interquartile range (IQR)1329

Descriptive statistics

Standard deviation997.14728
Coefficient of variation (CV)0.8383275
Kurtosis0.26853544
Mean1189.4484
Median Absolute Deviation (MAD)517
Skewness1.1094657
Sum1.2358844 × 108
Variance994302.7
MonotonicityNot monotonic
2025-10-22T16:56:14.629062image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
337660
 
0.6%
594395
 
0.4%
404392
 
0.4%
2475369
 
0.4%
862369
 
0.4%
447362
 
0.3%
236351
 
0.3%
192333
 
0.3%
399332
 
0.3%
308329
 
0.3%
Other values (3792)100012
96.3%
ValueCountFrequency (%)
318
 
< 0.1%
568
 
< 0.1%
67128
0.1%
7359
0.1%
7430
 
< 0.1%
761
 
< 0.1%
7741
 
< 0.1%
7830
 
< 0.1%
802
 
< 0.1%
827
 
< 0.1%
ValueCountFrequency (%)
498312
< 0.1%
496313
< 0.1%
48175
 
< 0.1%
450210
< 0.1%
424318
< 0.1%
400011
< 0.1%
39995
 
< 0.1%
39988
< 0.1%
39979
< 0.1%
39968
< 0.1%

InflightWifiService
Real number (ℝ)

High correlation  Zeros 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.7296832
Minimum0
Maximum5
Zeros3103
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size811.9 KiB
2025-10-22T16:56:14.686492image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3278295
Coefficient of variation (CV)0.48644088
Kurtosis-0.84616972
Mean2.7296832
Median Absolute Deviation (MAD)1
Skewness0.040408022
Sum283625
Variance1.7631311
MonotonicityNot monotonic
2025-10-22T16:56:14.734257image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
325868
24.9%
225830
24.9%
419794
19.1%
117840
17.2%
511469
11.0%
03103
 
3.0%
ValueCountFrequency (%)
03103
 
3.0%
117840
17.2%
225830
24.9%
325868
24.9%
419794
19.1%
511469
11.0%
ValueCountFrequency (%)
511469
11.0%
419794
19.1%
325868
24.9%
225830
24.9%
117840
17.2%
03103
 
3.0%

Departure/Arrival time convenient
Real number (ℝ)

Zeros 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.060296
Minimum0
Maximum5
Zeros5300
Zeros (%)5.1%
Negative0
Negative (%)0.0%
Memory size811.9 KiB
2025-10-22T16:56:14.782749image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.5250752
Coefficient of variation (CV)0.49834237
Kurtosis-1.0377673
Mean3.060296
Median Absolute Deviation (MAD)1
Skewness-0.33439863
Sum317977
Variance2.3258544
MonotonicityNot monotonic
2025-10-22T16:56:14.830644image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
425546
24.6%
522403
21.6%
317966
17.3%
217191
16.5%
115498
14.9%
05300
 
5.1%
ValueCountFrequency (%)
05300
 
5.1%
115498
14.9%
217191
16.5%
317966
17.3%
425546
24.6%
522403
21.6%
ValueCountFrequency (%)
522403
21.6%
425546
24.6%
317966
17.3%
217191
16.5%
115498
14.9%
05300
 
5.1%

Ease of Online booking
Real number (ℝ)

High correlation  Zeros 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.7569006
Minimum0
Maximum5
Zeros4487
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size811.9 KiB
2025-10-22T16:56:14.879171image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3989295
Coefficient of variation (CV)0.50742833
Kurtosis-0.91034621
Mean2.7569006
Median Absolute Deviation (MAD)1
Skewness-0.018294273
Sum286453
Variance1.9570037
MonotonicityNot monotonic
2025-10-22T16:56:14.927840image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
324449
23.5%
224021
23.1%
419571
18.8%
117525
16.9%
513851
13.3%
04487
 
4.3%
ValueCountFrequency (%)
04487
 
4.3%
117525
16.9%
224021
23.1%
324449
23.5%
419571
18.8%
513851
13.3%
ValueCountFrequency (%)
513851
13.3%
419571
18.8%
324449
23.5%
224021
23.1%
117525
16.9%
04487
 
4.3%

Gate location
Real number (ℝ)

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9768825
Minimum0
Maximum5
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size811.9 KiB
2025-10-22T16:56:14.975421image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.277621
Coefficient of variation (CV)0.42918087
Kurtosis-1.0302833
Mean2.9768825
Median Absolute Deviation (MAD)1
Skewness-0.058889412
Sum309310
Variance1.6323154
MonotonicityNot monotonic
2025-10-22T16:56:15.025968image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
328577
27.5%
424426
23.5%
219459
18.7%
117562
16.9%
513879
13.4%
01
 
< 0.1%
ValueCountFrequency (%)
01
 
< 0.1%
117562
16.9%
219459
18.7%
328577
27.5%
424426
23.5%
513879
13.4%
ValueCountFrequency (%)
513879
13.4%
424426
23.5%
328577
27.5%
219459
18.7%
117562
16.9%
01
 
< 0.1%

FoodandDrink
Real number (ℝ)

High correlation 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2021289
Minimum0
Maximum5
Zeros107
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size811.9 KiB
2025-10-22T16:56:15.074085image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3295327
Coefficient of variation (CV)0.41520275
Kurtosis-1.1454532
Mean3.2021289
Median Absolute Deviation (MAD)1
Skewness-0.1512795
Sum332714
Variance1.7676572
MonotonicityNot monotonic
2025-10-22T16:56:15.123881image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
424359
23.4%
522313
21.5%
322300
21.5%
221988
21.2%
112837
12.4%
0107
 
0.1%
ValueCountFrequency (%)
0107
 
0.1%
112837
12.4%
221988
21.2%
322300
21.5%
424359
23.4%
522313
21.5%
ValueCountFrequency (%)
522313
21.5%
424359
23.4%
322300
21.5%
221988
21.2%
112837
12.4%
0107
 
0.1%

Online boarding
Real number (ℝ)

High correlation  Zeros 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2503753
Minimum0
Maximum5
Zeros2428
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size811.9 KiB
2025-10-22T16:56:15.170333image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.349509
Coefficient of variation (CV)0.41518557
Kurtosis-0.7020058
Mean3.2503753
Median Absolute Deviation (MAD)1
Skewness-0.4538517
Sum337727
Variance1.8211744
MonotonicityNot monotonic
2025-10-22T16:56:15.220726image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
430762
29.6%
321804
21.0%
520713
19.9%
217505
16.8%
110692
 
10.3%
02428
 
2.3%
ValueCountFrequency (%)
02428
 
2.3%
110692
 
10.3%
217505
16.8%
321804
21.0%
430762
29.6%
520713
19.9%
ValueCountFrequency (%)
520713
19.9%
430762
29.6%
321804
21.0%
217505
16.8%
110692
 
10.3%
02428
 
2.3%

Seat comfort
Real number (ℝ)

High correlation 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.439396
Minimum0
Maximum5
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size811.9 KiB
2025-10-22T16:56:15.394857image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median4
Q35
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.3190875
Coefficient of variation (CV)0.38352302
Kurtosis-0.92570207
Mean3.439396
Median Absolute Deviation (MAD)1
Skewness-0.48277539
Sum357367
Variance1.7399919
MonotonicityNot monotonic
2025-10-22T16:56:15.444024image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
431765
30.6%
526470
25.5%
318696
18.0%
214897
14.3%
112075
 
11.6%
01
 
< 0.1%
ValueCountFrequency (%)
01
 
< 0.1%
112075
 
11.6%
214897
14.3%
318696
18.0%
431765
30.6%
526470
25.5%
ValueCountFrequency (%)
526470
25.5%
431765
30.6%
318696
18.0%
214897
14.3%
112075
 
11.6%
01
 
< 0.1%

Inflight entertainment
Real number (ℝ)

High correlation 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3581575
Minimum0
Maximum5
Zeros14
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size811.9 KiB
2025-10-22T16:56:15.494151image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median4
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3329907
Coefficient of variation (CV)0.39694109
Kurtosis-1.0606958
Mean3.3581575
Median Absolute Deviation (MAD)1
Skewness-0.36513059
Sum348926
Variance1.7768642
MonotonicityNot monotonic
2025-10-22T16:56:15.542921image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
429423
28.3%
525213
24.3%
319139
18.4%
217637
17.0%
112478
12.0%
014
 
< 0.1%
ValueCountFrequency (%)
014
 
< 0.1%
112478
12.0%
217637
17.0%
319139
18.4%
429423
28.3%
525213
24.3%
ValueCountFrequency (%)
525213
24.3%
429423
28.3%
319139
18.4%
217637
17.0%
112478
12.0%
014
 
< 0.1%

On-board service
Real number (ℝ)

High correlation 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3823626
Minimum0
Maximum5
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size811.9 KiB
2025-10-22T16:56:15.591614image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median4
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.2883544
Coefficient of variation (CV)0.38090368
Kurtosis-0.89233524
Mean3.3823626
Median Absolute Deviation (MAD)1
Skewness-0.42003075
Sum351441
Variance1.659857
MonotonicityNot monotonic
2025-10-22T16:56:15.640492image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
430867
29.7%
523648
22.8%
322833
22.0%
214681
14.1%
111872
 
11.4%
03
 
< 0.1%
ValueCountFrequency (%)
03
 
< 0.1%
111872
 
11.4%
214681
14.1%
322833
22.0%
430867
29.7%
523648
22.8%
ValueCountFrequency (%)
523648
22.8%
430867
29.7%
322833
22.0%
214681
14.1%
111872
 
11.4%
03
 
< 0.1%

Leg room service
Real number (ℝ)

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3510548
Minimum0
Maximum5
Zeros472
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size811.9 KiB
2025-10-22T16:56:15.687885image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median4
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3156046
Coefficient of variation (CV)0.39259418
Kurtosis-0.98025691
Mean3.3510548
Median Absolute Deviation (MAD)1
Skewness-0.35023134
Sum348188
Variance1.7308155
MonotonicityNot monotonic
2025-10-22T16:56:15.738635image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
428789
27.7%
524667
23.7%
320098
19.3%
219525
18.8%
110353
 
10.0%
0472
 
0.5%
ValueCountFrequency (%)
0472
 
0.5%
110353
 
10.0%
219525
18.8%
320098
19.3%
428789
27.7%
524667
23.7%
ValueCountFrequency (%)
524667
23.7%
428789
27.7%
320098
19.3%
219525
18.8%
110353
 
10.0%
0472
 
0.5%

Baggage handling
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.0 MiB
4
37383 
5
27131 
3
20632 
2
11521 
1
7237 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters103904
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row3
3rd row4
4th row3
5th row4

Common Values

ValueCountFrequency (%)
437383
36.0%
527131
26.1%
320632
19.9%
211521
 
11.1%
17237
 
7.0%

Length

2025-10-22T16:56:15.796494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-10-22T16:56:15.842994image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
437383
36.0%
527131
26.1%
320632
19.9%
211521
 
11.1%
17237
 
7.0%

Most occurring characters

ValueCountFrequency (%)
437383
36.0%
527131
26.1%
320632
19.9%
211521
 
11.1%
17237
 
7.0%

Most occurring categories

ValueCountFrequency (%)
(unknown)103904
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
437383
36.0%
527131
26.1%
320632
19.9%
211521
 
11.1%
17237
 
7.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown)103904
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
437383
36.0%
527131
26.1%
320632
19.9%
211521
 
11.1%
17237
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown)103904
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
437383
36.0%
527131
26.1%
320632
19.9%
211521
 
11.1%
17237
 
7.0%

CheckinService
Real number (ℝ)

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3042905
Minimum0
Maximum5
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size811.9 KiB
2025-10-22T16:56:15.892456image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2653958
Coefficient of variation (CV)0.38295538
Kurtosis-0.82887706
Mean3.3042905
Median Absolute Deviation (MAD)1
Skewness-0.36498196
Sum343329
Variance1.6012266
MonotonicityNot monotonic
2025-10-22T16:56:15.943162image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
429055
28.0%
328446
27.4%
520619
19.8%
212893
12.4%
112890
12.4%
01
 
< 0.1%
ValueCountFrequency (%)
01
 
< 0.1%
112890
12.4%
212893
12.4%
328446
27.4%
429055
28.0%
520619
19.8%
ValueCountFrequency (%)
520619
19.8%
429055
28.0%
328446
27.4%
212893
12.4%
112890
12.4%
01
 
< 0.1%

Inflight service
Real number (ℝ)

High correlation 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6404277
Minimum0
Maximum5
Zeros3
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size811.9 KiB
2025-10-22T16:56:15.990585image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median4
Q35
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.175663
Coefficient of variation (CV)0.3229464
Kurtosis-0.3575092
Mean3.6404277
Median Absolute Deviation (MAD)1
Skewness-0.69031396
Sum378255
Variance1.3821836
MonotonicityNot monotonic
2025-10-22T16:56:16.040700image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
437945
36.5%
527116
26.1%
320299
19.5%
211457
 
11.0%
17084
 
6.8%
03
 
< 0.1%
ValueCountFrequency (%)
03
 
< 0.1%
17084
 
6.8%
211457
 
11.0%
320299
19.5%
437945
36.5%
527116
26.1%
ValueCountFrequency (%)
527116
26.1%
437945
36.5%
320299
19.5%
211457
 
11.0%
17084
 
6.8%
03
 
< 0.1%

Cleanliness
Real number (ℝ)

High correlation 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2863509
Minimum0
Maximum5
Zeros12
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size811.9 KiB
2025-10-22T16:56:16.091145image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3122728
Coefficient of variation (CV)0.39931003
Kurtosis-1.0125577
Mean3.2863509
Median Absolute Deviation (MAD)1
Skewness-0.30007449
Sum341465
Variance1.72206
MonotonicityNot monotonic
2025-10-22T16:56:16.138838image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
427179
26.2%
324574
23.7%
522689
21.8%
216132
15.5%
113318
12.8%
012
 
< 0.1%
ValueCountFrequency (%)
012
 
< 0.1%
113318
12.8%
216132
15.5%
324574
23.7%
427179
26.2%
522689
21.8%
ValueCountFrequency (%)
522689
21.8%
427179
26.2%
324574
23.7%
216132
15.5%
113318
12.8%
012
 
< 0.1%

Departure Delay in Minutes
Real number (ℝ)

High correlation  Zeros 

Distinct446
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.815618
Minimum0
Maximum1592
Zeros58668
Zeros (%)56.5%
Negative0
Negative (%)0.0%
Memory size811.9 KiB
2025-10-22T16:56:16.204797image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q312
95-th percentile78
Maximum1592
Range1592
Interquartile range (IQR)12

Descriptive statistics

Standard deviation38.230901
Coefficient of variation (CV)2.5804458
Kurtosis100.26701
Mean14.815618
Median Absolute Deviation (MAD)0
Skewness6.7339795
Sum1539402
Variance1461.6018
MonotonicityNot monotonic
2025-10-22T16:56:16.286059image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
058668
56.5%
12948
 
2.8%
22274
 
2.2%
32009
 
1.9%
41854
 
1.8%
51692
 
1.6%
61517
 
1.5%
71392
 
1.3%
81295
 
1.2%
91255
 
1.2%
Other values (436)29000
27.9%
ValueCountFrequency (%)
058668
56.5%
12948
 
2.8%
22274
 
2.2%
32009
 
1.9%
41854
 
1.8%
51692
 
1.6%
61517
 
1.5%
71392
 
1.3%
81295
 
1.2%
91255
 
1.2%
ValueCountFrequency (%)
15921
< 0.1%
13051
< 0.1%
10171
< 0.1%
9781
< 0.1%
9331
< 0.1%
9301
< 0.1%
9211
< 0.1%
8591
< 0.1%
8531
< 0.1%
7501
< 0.1%

Arrival Delay in Minutes
Real number (ℝ)

High correlation  Zeros 

Distinct455
Distinct (%)0.4%
Missing310
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean15.178678
Minimum0
Maximum1584
Zeros58159
Zeros (%)56.0%
Negative0
Negative (%)0.0%
Memory size811.9 KiB
2025-10-22T16:56:16.365179image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q313
95-th percentile79
Maximum1584
Range1584
Interquartile range (IQR)13

Descriptive statistics

Standard deviation38.698682
Coefficient of variation (CV)2.5495423
Kurtosis94.537006
Mean15.178678
Median Absolute Deviation (MAD)0
Skewness6.5966368
Sum1572420
Variance1497.588
MonotonicityNot monotonic
2025-10-22T16:56:16.446735image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
058159
56.0%
12211
 
2.1%
22064
 
2.0%
31952
 
1.9%
41907
 
1.8%
51658
 
1.6%
61616
 
1.6%
71481
 
1.4%
81394
 
1.3%
91264
 
1.2%
Other values (445)29888
28.8%
ValueCountFrequency (%)
058159
56.0%
12211
 
2.1%
22064
 
2.0%
31952
 
1.9%
41907
 
1.8%
51658
 
1.6%
61616
 
1.6%
71481
 
1.4%
81394
 
1.3%
91264
 
1.2%
ValueCountFrequency (%)
15841
< 0.1%
12801
< 0.1%
10111
< 0.1%
9701
< 0.1%
9521
< 0.1%
9241
< 0.1%
9201
< 0.1%
8601
< 0.1%
8231
< 0.1%
7291
< 0.1%

satisfaction
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size6.5 MiB
neutral or dissatisfied
58879 
satisfied
45025 

Length

Max length23
Median length23
Mean length16.933342
Min length9

Characters and Unicode

Total characters1759442
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowneutral or dissatisfied
2nd rowneutral or dissatisfied
3rd rowsatisfied
4th rowneutral or dissatisfied
5th rowsatisfied

Common Values

ValueCountFrequency (%)
neutral or dissatisfied58879
56.7%
satisfied45025
43.3%

Length

2025-10-22T16:56:16.521815image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-10-22T16:56:16.562517image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
neutral58879
26.6%
or58879
26.6%
dissatisfied58879
26.6%
satisfied45025
20.3%

Most occurring characters

ValueCountFrequency (%)
s266687
15.2%
i266687
15.2%
a162783
9.3%
t162783
9.3%
e162783
9.3%
d162783
9.3%
117758
6.7%
r117758
6.7%
f103904
 
5.9%
u58879
 
3.3%
Other values (3)176637
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown)1759442
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s266687
15.2%
i266687
15.2%
a162783
9.3%
t162783
9.3%
e162783
9.3%
d162783
9.3%
117758
6.7%
r117758
6.7%
f103904
 
5.9%
u58879
 
3.3%
Other values (3)176637
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1759442
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s266687
15.2%
i266687
15.2%
a162783
9.3%
t162783
9.3%
e162783
9.3%
d162783
9.3%
117758
6.7%
r117758
6.7%
f103904
 
5.9%
u58879
 
3.3%
Other values (3)176637
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1759442
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s266687
15.2%
i266687
15.2%
a162783
9.3%
t162783
9.3%
e162783
9.3%
d162783
9.3%
117758
6.7%
r117758
6.7%
f103904
 
5.9%
u58879
 
3.3%
Other values (3)176637
10.0%

Interactions

2025-10-22T16:56:10.722885image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:45.823426image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:47.244238image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:48.636401image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:49.967647image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:51.364962image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:52.626521image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:54.017810image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:55.303962image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:56.674798image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:57.934908image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:59.329620image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:00.651618image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:02.154326image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:03.462216image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:04.923986image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:06.287688image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:07.895346image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:09.222428image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:10.794967image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:45.944353image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:47.312565image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:48.708512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:50.138149image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:51.430625image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:52.806054image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:54.085379image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:55.372796image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:56.743805image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:58.000603image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:59.402013image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:00.720459image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:02.223905image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:03.530737image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:04.998966image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:06.355275image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:07.975569image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:09.294861image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:10.869846image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:46.015911image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:47.380949image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:48.777400image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:50.206850image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:51.499420image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:52.873756image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:54.155672image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:55.440200image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:56.811555image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:58.069814image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:59.474846image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:00.793820image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:02.295686image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:03.599399image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:05.072572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:06.427065image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:08.062840image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:09.368171image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:10.943808image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:46.087269image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:47.449915image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:48.847631image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:50.274314image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:51.568512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:52.943300image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:54.225948image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:55.509304image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:56.880752image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:58.138596image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:59.549385image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:00.865647image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:02.365409image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:03.670513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:05.146671image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:06.505350image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:08.155889image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:09.442365image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:11.017829image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:46.159182image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:47.518152image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:48.915839image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:50.340635image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:51.635323image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:53.011178image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:54.291608image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:55.689335image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:56.946549image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:58.211027image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:59.621921image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:00.937465image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:02.434014image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:03.738121image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:05.214421image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:06.585372image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:08.227203image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:09.513376image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:11.088622image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:46.229839image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:47.669323image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:48.993655image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:50.406382image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:51.699378image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:53.075971image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:54.358347image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:55.754587image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:57.010858image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:58.400710image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:59.692805image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:01.013228image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:02.502191image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:03.805993image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:05.278499image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:06.655842image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:08.294794image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:09.585223image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:11.162939image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:46.319174image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:47.739199image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:49.062223image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:50.481090image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:51.765078image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:53.141935image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:54.422997image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:55.819363image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:57.078123image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:58.465822image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:59.763026image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:01.097544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:02.573387image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:03.872792image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:05.345315image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:06.741695image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:08.360910image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:09.657152image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:11.246147image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:46.395571image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:47.806796image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:49.131531image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:50.554048image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:51.831206image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:53.211038image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:54.488638image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:55.883611image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:57.142494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:58.531016image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:59.833043image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:01.166139image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:02.640009image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:03.938941image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:05.413772image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:06.813623image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:08.428683image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:09.729266image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:11.328830image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:46.471683image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:47.874238image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:49.198772image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:50.621407image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:51.894630image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:53.276576image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:54.552845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:55.946107image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:57.206819image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:58.594584image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:59.898458image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:01.256387image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:02.706578image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:04.007796image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:05.491647image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:06.886715image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:08.492917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:09.799360image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:11.398883image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:46.542048image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:47.940138image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:49.266313image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:50.686694image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:51.959677image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:53.343359image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:54.618294image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:56.010485image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:57.269831image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:58.659143image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:59.965158image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:01.445077image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:02.774753image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:04.089288image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:05.565660image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:06.954957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:08.559327image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:09.873516image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:11.471550image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:46.609437image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:48.008668image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:49.333557image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:50.752726image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:52.023782image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:53.408208image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:54.683756image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:56.073916image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:57.335009image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:58.722294image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:00.031146image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:01.515766image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:02.841562image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:04.277576image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:05.640085image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:07.121166image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:08.622929image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:09.948417image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:11.542338image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:46.675654image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:48.075143image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:49.401752image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:50.818602image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:52.089142image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:53.474530image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:54.755231image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:56.137553image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:57.398853image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:58.787292image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:00.095593image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:01.583439image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:02.909348image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:04.342696image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:05.711985image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:07.189449image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:08.690489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:10.020690image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:11.614850image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:46.742106image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:48.145278image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:49.470396image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:50.884912image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:52.153309image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:53.540235image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:54.823407image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:56.203892image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:57.464399image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:58.851494image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:00.163389image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:01.653511image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:02.973730image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:04.409688image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:05.787190image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:07.257184image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:08.757461image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:10.091716image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:11.686509image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:46.814613image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:48.212821image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:49.539480image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:50.951986image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:52.219216image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:53.607669image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:54.890281image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:56.268128image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:57.530939image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:58.916992image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:00.229008image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:01.723421image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:03.039864image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:04.474587image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:05.859530image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:07.323472image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:08.821550image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:10.164204image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:11.758861image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:46.881567image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:48.281917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:49.607448image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:51.018079image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:52.283432image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:53.674329image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:54.958890image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:56.334996image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:57.594932image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:58.981141image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:00.298645image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:01.792997image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:03.104171image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:04.542847image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:05.927950image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:07.515603image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:08.886699image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:10.355626image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:11.831854image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:46.960409image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:48.348673image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:49.675661image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:51.086222image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:52.349218image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:53.741208image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:55.027782image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:56.399347image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:57.660828image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:59.047061image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:00.363810image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:01.863427image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:03.184815image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:04.610086image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:06.000034image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:07.580453image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:08.949862image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:10.427549image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:11.910507image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:47.026866image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:48.418295image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:49.744365image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:51.152150image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:52.413562image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:53.806962image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:55.094010image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:56.465051image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:57.724408image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:59.110589image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:00.433633image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:01.930981image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:03.250264image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:04.681155image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:06.066683image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:07.651493image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:09.016287image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:10.498373image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:11.983668image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:47.095265image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:48.485133image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:49.812720image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:51.218842image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:52.477873image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:53.871525image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:55.158163image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:56.529013image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:57.789815image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:59.176129image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:00.498942image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:01.999181image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:03.315250image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:04.755267image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:06.135484image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:07.718379image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:09.078640image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:10.570340image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:12.062381image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:47.169721image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:48.562560image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:49.891474image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:51.291393image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:52.552890image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:53.946215image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:55.232056image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:56.603347image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:57.861943image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:55:59.248605image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:00.575140image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:02.076636image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:03.389819image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:04.842561image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:06.211398image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:07.818456image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:09.151704image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-10-22T16:56:10.646348image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-10-22T16:56:16.620877image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
AgeArrival Delay in MinutesBaggage handlingCheckinServiceClassCleanlinessCustomerTypeDeparture Delay in MinutesDeparture/Arrival time convenientEase of Online bookingFlightDistanceFoodandDrinkGate locationGenderInflight entertainmentInflight serviceInflightWifiServiceLeg room serviceOn-board serviceOnline boardingSeat comfortTypeofTravelUnnamed: 0idsatisfaction
Age1.000-0.0120.0610.0400.2070.0540.375-0.0110.0360.0230.0720.021-0.0020.0140.082-0.0310.0170.0520.0700.2160.1610.3400.0050.0260.284
Arrival Delay in Minutes-0.0121.0000.006-0.0350.000-0.0310.0000.741-0.006-0.014-0.001-0.0330.0050.008-0.044-0.055-0.037-0.020-0.048-0.050-0.0370.000-0.004-0.0050.017
Baggage handling0.0610.0061.0000.1420.1350.0630.0670.0070.0720.0320.0370.0360.0540.0480.3520.4910.1200.2670.3990.0930.0820.0510.0000.0640.288
CheckinService0.040-0.0350.1421.0000.1260.1750.033-0.0180.1000.0110.0720.084-0.0360.0110.1210.2500.0430.1450.2350.2180.1990.019-0.0040.0750.249
Class0.2070.0000.1350.1261.0000.1150.1230.0000.1000.1160.3440.0770.1110.0120.1520.1310.1020.1630.1600.2490.1750.5540.0000.1290.505
Cleanliness0.054-0.0310.0630.1750.1151.0000.105-0.0160.0140.0150.0810.647-0.0040.0180.6810.1010.1310.0970.1250.3460.6670.093-0.0020.0230.314
CustomerType0.3750.0000.0670.0330.1230.1051.0000.0000.2930.0550.2480.0790.1250.0320.1200.0550.0370.0760.0770.1950.1730.3080.0060.0140.188
Departure Delay in Minutes-0.0110.7410.007-0.0180.000-0.0160.0001.000-0.003-0.0110.027-0.0210.0040.006-0.027-0.032-0.030-0.006-0.027-0.033-0.0200.000-0.0060.0570.017
Departure/Arrival time convenient0.036-0.0060.0720.1000.1000.0140.293-0.0031.0000.440-0.0130.0030.4500.009-0.0090.0910.3390.0070.0720.0620.0120.2900.000-0.0030.066
Ease of Online booking0.023-0.0140.0320.0110.1160.0150.055-0.0110.4401.0000.0660.0300.4620.0060.0430.0350.7120.0950.0370.3680.0270.1890.0020.0120.316
FlightDistance0.072-0.0010.0370.0720.3440.0810.2480.027-0.0130.0661.0000.0470.0010.0100.1050.0600.0060.1180.1000.1940.1370.2810.0030.1330.312
FoodandDrink0.021-0.0330.0360.0840.0770.6470.079-0.0210.0030.0300.0471.000-0.0010.0100.6100.0440.1330.0310.0580.2410.5580.076-0.003-0.0010.224
Gate location-0.0020.0050.054-0.0360.111-0.0040.1250.0040.4500.4620.001-0.0011.0000.0070.003-0.0070.333-0.006-0.028-0.0010.0020.1550.004-0.0010.155
Gender0.0140.0080.0480.0110.0120.0180.0320.0060.0090.0060.0100.0100.0071.0000.0060.0460.0080.0540.0220.0440.0350.0060.0000.0070.012
Inflight entertainment0.082-0.0440.3520.1210.1520.6810.120-0.027-0.0090.0430.1050.6100.0030.0061.0000.4220.2000.3140.4370.3020.6040.1650.0010.0020.422
Inflight service-0.031-0.0550.4910.2500.1310.1010.055-0.0320.0910.0350.0600.044-0.0070.0460.4221.0000.1050.3730.5690.1090.0980.041-0.0000.0740.282
InflightWifiService0.017-0.0370.1200.0430.1020.1310.037-0.0300.3390.7120.0060.1330.3330.0080.2000.1051.0000.1500.1170.4360.1190.183-0.003-0.0230.525
Leg room service0.052-0.0200.2670.1450.1630.0970.076-0.0060.0070.0950.1180.031-0.0060.0540.3140.3730.1501.0000.3640.1390.1200.1710.0050.0420.344
On-board service0.070-0.0480.3990.2350.1600.1250.077-0.0270.0720.0370.1000.058-0.0280.0220.4370.5690.1170.3641.0000.1760.1470.0870.0010.0520.333
Online boarding0.216-0.0500.0930.2180.2490.3460.195-0.0330.0620.3680.1940.241-0.0010.0440.3020.1090.4360.1390.1761.0000.4400.2380.0010.0560.618
Seat comfort0.161-0.0370.0820.1990.1750.6670.173-0.0200.0120.0270.1370.5580.0020.0350.6040.0980.1190.1200.1470.4401.0000.133-0.0010.0540.389
TypeofTravel0.3400.0000.0510.0190.5540.0930.3080.0000.2900.1890.2810.0760.1550.0060.1650.0410.1830.1710.0870.2380.1331.0000.0000.0190.449
Unnamed: 00.005-0.0040.000-0.0040.000-0.0020.006-0.0060.0000.0020.003-0.0030.0040.0000.001-0.000-0.0030.0050.0010.001-0.0010.0001.0000.0030.006
id0.026-0.0050.0640.0750.1290.0230.0140.057-0.0030.0120.133-0.001-0.0010.0070.0020.074-0.0230.0420.0520.0560.0540.0190.0031.0000.025
satisfaction0.2840.0170.2880.2490.5050.3140.1880.0170.0660.3160.3120.2240.1550.0120.4220.2820.5250.3440.3330.6180.3890.4490.0060.0251.000

Missing values

2025-10-22T16:56:12.216847image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-10-22T16:56:12.547198image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Unnamed: 0idGenderCustomerTypeAgeTypeofTravelClassFlightDistanceInflightWifiServiceDeparture/Arrival time convenientEase of Online bookingGate locationFoodandDrinkOnline boardingSeat comfortInflight entertainmentOn-board serviceLeg room serviceBaggage handlingCheckinServiceInflight serviceCleanlinessDeparture Delay in MinutesArrival Delay in Minutessatisfaction
0070172MaleLoyal Customer13Personal TravelEco Plus460343153554344552518.0neutral or dissatisfied
115047Maledisloyal Customer25Business travelBusiness2353233131115314116.0neutral or dissatisfied
22110028FemaleLoyal Customer26Business travelBusiness11422222555543444500.0satisfied
3324026FemaleLoyal Customer25Business travelBusiness56225552222253142119.0neutral or dissatisfied
44119299MaleLoyal Customer61Business travelBusiness2143333455334433300.0satisfied
55111157FemaleLoyal Customer26Personal TravelEco11803421121134444100.0neutral or dissatisfied
6682113MaleLoyal Customer47Personal TravelEco127624232222334352923.0neutral or dissatisfied
7796462FemaleLoyal Customer52Business travelBusiness20354344555555545440.0satisfied
8879485FemaleLoyal Customer41Business travelBusiness8531222433112141200.0neutral or dissatisfied
9965725Maledisloyal Customer20Business travelEco10613334233223443200.0neutral or dissatisfied
Unnamed: 0idGenderCustomerTypeAgeTypeofTravelClassFlightDistanceInflightWifiServiceDeparture/Arrival time convenientEase of Online bookingGate locationFoodandDrinkOnline boardingSeat comfortInflight entertainmentOn-board serviceLeg room serviceBaggage handlingCheckinServiceInflight serviceCleanlinessDeparture Delay in MinutesArrival Delay in Minutessatisfaction
10389410389486549MaleLoyal Customer26Business travelBusiness712444455553443451726.0satisfied
10389510389566030Femaledisloyal Customer24Business travelEco1055111211113355411310.0neutral or dissatisfied
10389610389671445MaleLoyal Customer57Business travelEco8674555444434313400.0neutral or dissatisfied
103897103897102203FemaleLoyal Customer60Business travelBusiness15995555554444444497.0satisfied
10389810389860666MaleLoyal Customer50Personal TravelEco16203134232243424200.0neutral or dissatisfied
10389910389994171Femaledisloyal Customer23Business travelEco1922123222231423230.0neutral or dissatisfied
10390010390073097MaleLoyal Customer49Business travelBusiness23474444245555555400.0satisfied
10390110390168825Maledisloyal Customer30Business travelBusiness199511134154324554714.0neutral or dissatisfied
10390210390254173Femaledisloyal Customer22Business travelEco10001115111145154100.0neutral or dissatisfied
10390310390362567MaleLoyal Customer27Business travelBusiness17231333111111443100.0neutral or dissatisfied